opendata/fridge/match.py

63 lines
1.7 KiB
Python

from numpy.lib.function_base import average
import pandas as pd
df = pd.read_csv('./newResult0930.csv', index_col=0)
# df = pd.read_csv('./newResult.csv', index_col=0)
# df = df.dropna()
df['final_type'] = '0'
for index in df.index:
if df.loc[index, 'code'] in [31, 32]:
df.loc[index, 'final_type'] = 1
elif df.loc[index, 'code'] in [21, 22, 23, 24, 33, 34]:
df.loc[index, 'final_type'] = 2
elif df.loc[index, 'code'] in [11, 12, 13, 14]:
df.loc[index, 'final_type'] = 3
else:
df.loc[index, 'final_type'] = 4
# df.to_csv('test_r.csv')
# print(df)
res_total_level = [[0 for i in range(4)] for i in range(4)]
res_INQUIRY_level = [[0 for i in range(4)] for i in range(4)]
total_score = [[] for i in range(4)]
INQUIRY_score = [[] for i in range(4)]
for index in df.index:
res_total_level[int(df.loc[index, 'total_level'] - 1)
][df.loc[index, 'final_type'] - 1] += 1
res_INQUIRY_level[int(df.loc[index, 'INQUIRY_level'] - 1)
][df.loc[index, 'final_type'] - 1] += 1
total_score[df.loc[index, 'final_type'] -
1].append(df.loc[index, 'total_score'])
INQUIRY_score[df.loc[index, 'final_type'] -
1].append(df.loc[index, 'INQUIRY_score'])
# print(df.loc[index])
# print(res_total_level)
# print(res_INQUIRY_level)
# print(total_score)
# print(INQUIRY_score)
print("res_total_level")
for i in res_total_level:
print(i, sum(i))
for j in i:
print(j/sum(i))
print("res_INQUIRY_level")
for i in res_INQUIRY_level:
print(i, sum(i))
for j in i:
print(j/sum(i))
print("total_score")
for i in total_score:
print(average(i))
print("INQUIRY_score")
for i in INQUIRY_score:
print(average(i))